The data on Apollo[1]} includes 10500 discrete frames of monocular RGB images and corresponding 3D lane ground truth, which are split into three scenes: balanced, rally observed, and visual variation scenes. Each scene contains independent training sets and test sets. It should be noted that because our virtual camera needs to use the external parameters of the camera, Apollo does not provide specific external parameters of the camera. We calculate the intrinsic and extrinsic parameters of the camera through the height and pitch of camera provided by the dataset. In Table.REF , we give a comparison between the work of the foreword and our work. Our model has trained 80 epochs on these datasets. The results of our work for F1-score and X error both reached the state-of-the-art on apollo. However, because we work more focused on the BEV plane, our work does not perform well on Z error. We will improve this shortcoming in the future.
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